الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Question Answering On Trecqa

المقاييس

MAP

MRR

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	MAP	MRR	Paper Title	Repository
Contextual DeBERTa-V3-Large + SSP	0.919	0.945	Context-Aware Transformer Pre-Training for Answer Sentence Selection	-
CNN	0.711	0.785	Deep Learning for Answer Sentence Selection
NLP-Capsule	0.7773	0.7416	Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications
DeBERTa-V3-Large + SSP	0.923	0.946	Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection	-
aNMM	0.750	0.811	aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model
HyperQA	0.770	0.825	Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
RoBERTa-Base Joint + MSPP	0.911	0.952	Paragraph-based Transformer Pre-training for Multi-Sentence Inference
RoBERTa-Base + PSD	0.903	0.951	Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection	-
PWIN	0.7588	0.8219	-	-
TANDA DeBERTa-V3-Large + ALL	0.954	0.984	Structural Self-Supervised Objectives for Transformers	-
Comp-Clip + LM + LC	0.868	0.928	A Compare-Aggregate Model with Latent Clustering for Answer Selection	-
TANDA-RoBERTa (ASNQ, TREC-QA)	0.943	0.974	TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection	-
RLAS-BIABC	0.913	0.998	RLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm	-

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Question Answering On Trecqa | SOTA | HyperAI